Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild type primary glioblastoma

We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy.

Type: Other
Archiver: European Genome-Phenome Archive (EGA)

1 Dataset 1 Publication

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID	Description	Technology	Samples
EGAD00001010156	We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy.	Illumina HiSeq 2500	113

Publications	Citations
Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild-type primary glioblastoma. Nam Y, Koo H, Yang Y, Shin S, Zhu Z, Kim D, Cho HJ, Mu Q, Choi SW, Sa JK, Seo YJ, Kim Y, Lee K, Oh JW, Kwon YJ, Park WY, Kong DS, Seol HJ, Lee JI, Park CK, Lee HW, Yoon Y, Wang J. Genome Med 15: 2023 16	6